Skip to main content
Glama

DataNexus MCP

by com.datanexusmcp

nonprofit_fetch_nonprofit_financial_trends

Read-onlyIdempotent

5-year financial trend for any US nonprofit. Revenue growth, expense ratios, reserve trajectory, and health score history from IRS Form 990 data via ProPublica. Returns trend_direction (GROWING/STABLE/DECLINING/VOLATILE/INSUFFICIENT_DATA), CAGR, and year-by-year revenue, expense, and asset trends. years parameter: 1–10, default 5. Rate limit: 30/minute. No auth required. Complements nonprofit_fetch_nonprofit_full_profile by adding multi-year context. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="nonprofit_fetch_nonprofit_financial_trends", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
einYesEIN in format XX-XXXXXXX e.g. 46-5734087. Required.
yearsNoNumber of years of trend data 1-10. Default 5. Optional.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.4/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate read-only and idempotent. Description adds critical context: data source (ProPublica IRS Form 990), rate limit (30/min), no auth required, and return format (trend_direction, CAGR, etc.). No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is well-organized: purpose, returns, parameters, rate limit, auth, sibling relation, feedback fallback. Each sentence adds value, but it is slightly verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema, the description provides sufficient high-level output details, data source, rate limit, auth, and feedback mechanism. It is complete for a tool of this complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with both parameters fully described. Description repeats the default for years but does not add significant new semantic value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it provides a 5-year financial trend for US nonprofits, listing specific outputs like revenue growth, expense ratios, etc. It distinguishes itself from the sibling tool nonprofit_fetch_nonprofit_full_profile.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says it complements nonprofit_fetch_nonprofit_full_profile for multi-year context, and includes a feedback fallback if the tool doesn't serve the need. It does not explicitly state when not to use, but gives clear context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All DataNexus MCP toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0
Disambiguation4/5

Tools are grouped into clear domain prefixes (compliance, domain, frontend_security, etc.) with distinct purposes. Minor overlap exists between frontend_security_detect_typosquatting and security_detect_typosquatting, but descriptions clarify the different scope.

Naming Consistency4/5

Most tools follow a consistent verb_noun pattern with snake_case. Irregularities like 'fetch' vs 'audit' and two 'detect_typosquatting' tools exist, but overall naming is predictable within domains.

Tool Count3/5

55 tools is high for a single server given the breadth of domains. Some redundancy (e.g., two typosquatting tools) suggests possible trimming, but the count is justified by the wide coverage.

Completeness4/5

The tool surface covers key operations across domains like compliance, domain, security, legal, and nonprofit. Minor gaps exist, such as limited frontend audit beyond package.json and no general-purpose code scanning.

Resources